CN109655664A - A kind of stealing intelligent diagnosing method and equipment based on load characteristic model library - Google Patents
A kind of stealing intelligent diagnosing method and equipment based on load characteristic model library Download PDFInfo
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- CN109655664A CN109655664A CN201811507685.3A CN201811507685A CN109655664A CN 109655664 A CN109655664 A CN 109655664A CN 201811507685 A CN201811507685 A CN 201811507685A CN 109655664 A CN109655664 A CN 109655664A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R22/00—Arrangements for measuring time integral of electric power or current, e.g. electricity meters
- G01R22/06—Arrangements for measuring time integral of electric power or current, e.g. electricity meters by electronic methods
- G01R22/061—Details of electronic electricity meters
- G01R22/066—Arrangements for avoiding or indicating fraudulent use
Abstract
The embodiment of the present invention provides a kind of stealing intelligent diagnosing method and equipment based on load characteristic model library, this method comprises: obtain the electric energy meter of distribution transformer electric energy table and the corresponding n user of distribution transformer electric energy table multiple moment historical load data and n user electric energy meter multiple moment three-phase current data；Power distribution station is obtained in the management line loss at multiple moment according to historical load data；Management line loss at multiple moment of historical load data and power distribution station according to the electric energy meter of the corresponding n user of distribution transformer electric energy table at multiple moment obtains the relative coefficient of the management line loss of the corresponding historical load data of each user and power distribution station；Three-phase current data according to the electric energy meter of n user at multiple moment obtain the current imbalance rate of each user；Stealing suspicion user is determined according to the current imbalance rate of the relative coefficient and each user of the corresponding historical load data of each user and the management line loss of power distribution station, improves the efficiency and accuracy of stealing diagnosis.
Description
Technical field
The present invention relates to electric-power metering technical fields, and in particular to a kind of stealing based on load characteristic model library is intelligently examined
Disconnected method and apparatus.
Background technique
Means diversification situation is presented in electricity stealing in recent years, such as electronics new science and technology is applied to stealing by the enterprise having,
Ammeter password has been cracked, has been recompiled, by palm PC, ammeter of commanding behind the scenes is reversed, stalled, is slow etc., stealing main body
Legal entity, collective's stealing are developed to by personal stealing, the diversification further of stealing main body causes electric energy to be largely lost, and upsets
Normal electricity consumption order, compromises the legitimate rights and interests of power supply enterprise, and social equity justice is caused to lack.
Existing stealing diagnostic method is by the way of manually checking, not only low efficiency, but also general due to manually checking
It is to see whether the internal structure of ammeter appearance and table has the trace artificially changed, and it can only be it is judged whether or not stealing row
For, therefore accuracy is not high.
Summary of the invention
In view of this, the embodiment of the present invention propose a kind of stealing intelligent diagnosing method based on load characteristic model library and
Equipment, to solve the problems, such as existing stealing diagnostic method low efficiency and accuracy is not high.
To achieve the above object, the present invention adopts the following technical scheme:
According in a first aspect, the embodiment of the invention provides a kind of stealing intelligent diagnostics sides based on load characteristic model library
Method, which comprises obtain the electric energy meter of distribution transformer electric energy table and the corresponding n user of the distribution transformer electric energy table at multiple moment
Historical load data and the n user three-phase current data of the electric energy meter at the multiple moment, n be more than or equal to
1 integer；According to the distribution transformer electric energy table and electric energy meter the going through at multiple moment of the corresponding n user of the distribution transformer electric energy table
History load data obtains power distribution station in the management line loss at the multiple moment；According to the corresponding n use of the distribution transformer electric energy table
The electric energy meter at family, in the management line loss at the multiple moment, is obtained in the historical load data at multiple moment and the power distribution station
The relative coefficient of each corresponding historical load data of the user and the management line loss of the power distribution station；According to the n
The electric energy meter of user obtains the current imbalance rate of each user in the three-phase current data at the multiple moment；According to each
The relative coefficient and each user of the corresponding historical load data of user and the management line loss of the power distribution station
Current imbalance rate determines stealing suspicion user.
With reference to first aspect, in first aspect first embodiment, the power distribution station is obtained by following formula and is existed
The management line loss at the multiple moment:
Wherein, [L1, L2, L3..., Lm] indicate the management line loss of power distribution station moment 1 to the moment m, [dq1, dq2,
dq3..., dqm] indicate the historical load data of distribution transformer electric energy table moment 1 to the moment m, [q11, q21..., qn1] indicate when
Carve the historical load data of the electric energy meter of the 1 n user, [q12, q22..., qn2] indicate the moment 2 described in n user electricity
The historical load data of energy table, [q13, q23..., qn3] indicate the moment 3 described in n user electric energy meter historical load number
According to ..., [q1m, q2m..., qnm] indicate moment m described in n user electric energy meter historical load data.
First embodiment with reference to first aspect is obtained respectively in first aspect second embodiment by following formula
The relative coefficient of the corresponding historical load data of user and the management line loss of the power distribution station:
Wherein, [ρL1, ρL2, ρL3..., ρLn] respectively indicate the corresponding historical load data of the n user and the distribution
The relative coefficient of the management line loss in platform area, [q1i, q2i..., qni] indicate moment i described in n user electric energy meter history
Load data,Indicate first user in the average value of the power load at m moment,Indicate second user at m
The average value of the power load at quarter ...,Indicate average value of the nth user in the power load at m moment, LiFor distribution
Management line loss of the platform area in moment i,For power distribution station m moment average management line loss.
With reference to first aspect, first aspect first embodiment or first aspect second embodiment, in first aspect
In three embodiments, three-phase current data according to the electric energy meter of the n user at the multiple moment obtain each use
The current imbalance rate at family, comprising: the three-phase current data according to the electric energy meter of the n user at the multiple moment, point
Each user is not obtained in the average value of the three-phase current at each moment；According to the three-phase current data and each use
Family obtains each user in the current imbalance rate at each moment in the average value of the three-phase current at each moment；Root
Current imbalance rate according to each user at each moment obtains the current imbalance rate of each user.
Third embodiment with reference to first aspect is obtained respectively in the 4th embodiment of first aspect by following formula
Current imbalance rate of the user at each moment:
Wherein, imInmIndicate current imbalance rate of the nth user in moment m, iAnm、iBnmAnd iCnmIndicate nth user
In the three-phase current data of moment m,Indicate three-phase current iAnm、iBnmAnd iCnmAverage value.
4th embodiment with reference to first aspect is obtained respectively in the 5th embodiment of first aspect by following formula
The current imbalance rate of the user:
Wherein, [imI1, imI2, imI3..., imIn] indicate the current imbalance rate of the n user, [imI11, imI12,
imI13..., imI1m] indicate current imbalance rate of the 1st user m moment, [imI21, imI22, imI23..., imI2m]
Indicate current imbalance rate of the 2nd user m moment, [imI31, imI32, imI33..., imI3m] indicate that the 3rd user exists
The current imbalance rate ..., [imI at m momentn1, imIn2, imIn3..., imInm] indicate nth user in the electricity at m moment
Flow unbalance factor.
With reference to first aspect or first aspect first embodiment any embodiment party into the 5th embodiment of first aspect
Formula, in first aspect sixth embodiment, according to the corresponding historical load data of each user and the power distribution station
The relative coefficient of line loss and the current imbalance rate of each user are managed, determines stealing suspicion user, comprising: according to each institute
The relative coefficient of the management line loss of the corresponding historical load data of user and the power distribution station is stated, is determined described in being used to determine
The first set of stealing suspicion user；According to the current imbalance rate of each user, determine for determining the stealing suspicion
The second set of user；According to the first set and the second set, the stealing suspicion user is determined.
Sixth embodiment with reference to first aspect, it is corresponding according to each user in the 7th embodiment of first aspect
Historical load data and the power distribution station management line loss relative coefficient, determine for determining stealing suspicion use
The first set at family, comprising: judge the management line loss of the corresponding historical load data of each user and the power distribution station
Whether relative coefficient is greater than the first preset threshold；When the pipe of the user corresponding historical load data and the power distribution station
When the relative coefficient of lineation damage is greater than first preset threshold, determine that the user belongs to the first set.
7th embodiment with reference to first aspect, in the 8th embodiment of first aspect, according to the electricity of each user
Unbalance factor is flowed, determines the second set for determining the stealing suspicion user, comprising: judge the electric current of each user not
Whether balanced ratio is greater than the second preset threshold；When the current imbalance rate of the user is greater than second preset threshold, sentence
The fixed user belongs to the second set.
Sixth embodiment any embodiment into the 8th embodiment of first aspect with reference to first aspect, in first party
In the 9th embodiment of face, according to the first set and the second set, the stealing suspicion user is determined, comprising: root
According to the first set and the second set, the intersection of the first set and the second set is determined；Judge described
Whether the intersection of one set and the second set is empty set；When the intersection of the first set and the second set is not empty
When collection, determine that the user in the intersection is the stealing suspicion user.
9th embodiment with reference to first aspect, in the tenth embodiment of first aspect, when the first set and institute
When the intersection for stating second set is empty set, the union of the first set and the second set is determined；Judge first collection
It closes and whether the union of the second set is empty set；When the union of the first set and the second set is not empty set
When, determine that the user that is described and concentrating is the stealing suspicion user.
It is described computer-readable the embodiment of the invention provides a kind of computer readable storage medium according to second aspect
Storage medium is stored with computer instruction, and the computer instruction is for making the computer execute first aspect present invention or the
Stealing intelligent diagnosing method described in one side any embodiment.
According to the third aspect, the embodiment of the invention provides a kind of stealing intelligent diagnostics based on load characteristic model library to set
Standby, the equipment includes: memory and processor, and connection is communicated with each other between the memory and the processor, described to deposit
Computer instruction is stored in reservoir, the processor is by executing the computer instruction, thereby executing first party of the present invention
Stealing intelligent diagnosing method described in face or first aspect any embodiment.
Technical solution of the present invention at least has the advantages that compared with prior art
The embodiment of the present invention provides a kind of stealing intelligent diagnosing method and equipment based on load characteristic model library, this method
According to the distribution transformer electric energy table of acquisition and the electric energy meter of the corresponding n user of distribution transformer electric energy table multiple moment historical load data
Power distribution station is obtained in the management line loss at multiple moment, and according to the electric energy meter of the corresponding n user of distribution transformer electric energy table multiple
Management line loss of the historical load data and power distribution station at moment at multiple moment obtains the corresponding historical load data of each user
With the relative coefficient of the management line loss of power distribution station, according to the electric energy meter of n user of acquisition multiple moment three-phase electricity
Flow data obtains the current imbalance rate of each user, thus according to the pipe of each user corresponding historical load data and power distribution station
The relative coefficient of lineation damage and the current imbalance rate of each user determine stealing suspicion user, due to being existed with user's electric energy meter
Based on the load data of one period of history, current imbalance caused by electricity stealing, user power utilization load and Tai Qu are utilized
The features such as the strong correlation of line loss are managed, according to the relative coefficient and user of customer charge data and the management line loss of power distribution station
Current imbalance rate determine stealing suspicion user, data plane to electricity stealing carry out intelligent diagnostics, compared to existing
The mode manually checked improves the efficiency and accuracy of work of electricity anti-stealing.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, is also possible to obtain other drawings based on these drawings.
Fig. 1 is a specific example of the stealing intelligent diagnosing method based on load characteristic model library in the embodiment of the present invention
Flow chart；
Fig. 2 is the curve synoptic diagram of power distribution station line loss and user power utilization load in the embodiment of the present invention；
Fig. 3 is in the embodiment of the present invention one of step S4 in the stealing intelligent diagnosing method based on load characteristic model library
The flow chart of specific example；
Fig. 4 be the embodiment of the present invention in a user the current imbalance rate of a period of history schematic diagram；
Fig. 5 is in the embodiment of the present invention one of step S5 in the stealing intelligent diagnosing method based on load characteristic model library
The flow chart of specific example；
Fig. 6 is that another of the stealing intelligent diagnosing method based on load characteristic model library specifically shows in the embodiment of the present invention
The flow chart of example；
Fig. 7 is a specific example of the stealing intelligent diagnostics equipment based on load characteristic model library in the embodiment of the present invention
Schematic diagram.
Specific embodiment
Technical solution of the present invention is clearly and completely described below in conjunction with attached drawing, it is clear that described implementation
Example is a part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill
Personnel's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that term " first ", " second " are used for description purposes only, and cannot
It is interpreted as indication or suggestion relative importance.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It can
To be mechanical connection, it is also possible to be electrically connected；It can be directly connected, can also indirectly connected through an intermediary, it can be with
It is the connection inside two elements, can be wireless connection, be also possible to wired connection.For those of ordinary skill in the art
For, the concrete meaning of above-mentioned term in the present invention can be understood with concrete condition.
As long as in addition, the non-structure each other of technical characteristic involved in invention described below different embodiments
It can be combined with each other at conflict.
The embodiment of the invention provides a kind of stealing intelligent diagnosing methods based on load characteristic model library, as shown in Figure 1,
This method comprises:
Step S1: distribution transformer electric energy table and electric energy meter the going through at multiple moment of the corresponding n user of distribution transformer electric energy table are obtained
The three-phase current data of history load data and the electric energy meter of n user at multiple moment, n are the integer more than or equal to 1；Specifically
Ground can be the distribution transformer electric energy table for obtaining power distribution station and the corresponding n of distribution transformer electric energy table (n is more than or equal to 1 integer) a use
The three-phase current data of the electric energy meter of historical load data and n user of the electric energy meter at family within one month by a definite date time
(times of collection is m in one month).
Step S2: according to distribution transformer electric energy table and electric energy meter the going through at multiple moment of the corresponding n user of distribution transformer electric energy table
History load data obtains power distribution station in the management line loss at multiple moment；
Step S3: according to the electric energy meter of the corresponding n user of distribution transformer electric energy table multiple moment historical load data and
Power distribution station obtains the management line loss of the corresponding historical load data of each user and power distribution station in the management line loss at multiple moment
Relative coefficient；
Step S4: according to the electric energy meter of n user in the three-phase current data at multiple moment, the electric current of each user is obtained not
Balanced ratio；
Step S5: according to the relative coefficient of the corresponding historical load data of each user and the management line loss of power distribution station and
The current imbalance rate of each user determines stealing suspicion user.
S1 to step S5 through the above steps, the stealing intelligence provided in an embodiment of the present invention based on load characteristic model library
Diagnostic method, by user's electric energy meter based on the load data of a period of history, not using electric current caused by electricity stealing
The features such as the strong correlation of balance, user power utilization load and unit-area management line loss, according to the pipe of customer charge data and power distribution station
The relative coefficient and the current imbalance rate of user of lineation damage determine stealing suspicion user, data plane to electricity stealing into
Row intelligent diagnostics improve the efficiency and accuracy of work of electricity anti-stealing compared to the existing mode manually checked.
In specific embodiment of the present invention, power distribution station is obtained in the management line at multiple moment by following formula
Damage:
Wherein, [L1, L2, L3..., Lm] indicate power distribution station moment 1 to moment m management line loss, [dq1, dq2,
dq3..., dqm] indicate distribution transformer electric energy table moment 1 to moment m historical load data, [q11, q21..., qn1] indicate the moment 1
The historical load data of the electric energy meter of the n user, [q12, q22..., qn2] indicate the moment 2 described in n user electric energy meter
Historical load data, [q13, q23..., qn3] indicate the moment 3 described in n user electric energy meter historical load data ...,
[q1m, q2m..., qnm] indicate moment m described in n user electric energy meter historical load data.
In a specific embodiment of the invention, as shown in Fig. 2, by the power load of each user in power distribution station,
The management line loss of power distribution station depicts curve as, then power distribution station corresponding 1 curve of management line loss data (corresponds to curve
1), the power load data of n user just correspond to n curve (in Fig. 2 by taking two users as an example, corresponding to curve 2 and curve
3) the corresponding curve of the power load data curve corresponding with power distribution station management line loss data of n user, is calculated separately
Relative coefficient to get to the relative coefficient of the management line loss of the corresponding historical load data of each user and power distribution station, by
Significantly decline by a relatively large margin in the power load appearance that electricity stealing will lead to the user, and power distribution station manages line loss simultaneously
Then correspondingly occur significantly increasing considerably, therefore, the relative coefficient of user power utilization load and power distribution station management line loss
It is able to reflect electricity stealing, user power utilization load and the relative coefficient of power distribution station management line loss specifically can be by following
Formula calculates:
Wherein, [ρL1, ρL2, ρL3..., ρLn] respectively indicate the pipe of n user corresponding historical load data and power distribution station
The relative coefficient of lineation damage, [q1i, q2i..., qni] indicate moment i described in n user electric energy meter historical load data,Indicate first user in the average value of the power load at m moment,Indicate second user in the electricity consumption at m moment
The average value of load ...,Indicate average value of the nth user in the power load at m moment, LiFor power distribution station when
Management line loss when i is carved,For power distribution station m moment average management line loss.
It should be noted that calculating power load mean value according to the historical load data of user's electric energy meter and according to distribution
It is to be easy to calculate according to common sense that management line loss calculation of the platform area at each moment, which averagely manages line loss, and the embodiment of the present invention is no longer detailed
It states.
In a specific embodiment of the invention, as shown in figure 3, above-mentioned step S4, exists according to the electric energy meter of n user
The three-phase current data at multiple moment obtain the current imbalance rate of each user, specifically include:
Step S41: the three-phase current data according to the electric energy meter of n user at multiple moment respectively obtain each user and exist
The average value of the three-phase current at each moment；Specifically, for a user, the user each moment three-phase current it is flat
Mean value is to be obtained with the sum of value of each moment three-phase current divided by data bulk (i.e. time quantity).
Step S42: according to three-phase current data and each user in the average value of the three-phase current at each moment, each user is obtained
In the current imbalance rate at each moment；
Specifically, the maximum value of absolute value of the difference of three-phase current and phase current mean value and the ratio of phase current are exactly this
Current imbalance rate of the user at the moment obtains each user in the current imbalance rate at each moment by following formula:
Wherein, imInmIndicate current imbalance rate of the nth user in moment m, iAnm、iBnmAnd iCnmIndicate nth user
In the three-phase current data of moment m,Indicate three-phase current iAnm、iBnmAnd iCnmAverage value.
The current imbalance rate of user at various moments is drawn in line chart, as shown in figure 4, can intuitively reflect user
In the current imbalance rate of a period of history.
Step S43: the current imbalance rate according to each user at each moment obtains the current imbalance rate of each user；
Specifically, the current imbalance rate of each user is obtained by following formula:
Wherein, [imI1, imI2, imI3..., imIn] indicate n user current imbalance rate, [imI11, imI12,
imI13..., imI1m] indicate current imbalance rate of the 1st user m moment, [imI21, imI22, imI23..., imI2m]
Indicate current imbalance rate of the 2nd user m moment, [imI31, imI32, imI33..., imI3m] indicate that the 3rd user exists
The current imbalance rate ..., [imI at m momentn1, imIn2, imIn3..., imInm] indicate nth user in the electricity at m moment
Flow unbalance factor.
In a specific embodiment of the invention, as shown in figure 5, above-mentioned step S5, according to the corresponding history of each user
The relative coefficient of the management line loss of load data and power distribution station and the current imbalance rate of each user determine that stealing suspicion is used
Family specifically includes:
Step S51: according to the relative coefficient of the corresponding historical load data of each user and the management line loss of power distribution station,
Determine the first set for determining stealing suspicion user；It specifically can be and judge the corresponding historical load data of each user and match
Whether the relative coefficient of the management line loss of radio area is greater than the first preset threshold, which can be 0.8, when with
When the relative coefficient of the corresponding historical load data in family and the management line loss of power distribution station is greater than 0.8, determine that the user belongs to
First set.In other embodiments of the invention, the first preset threshold is also possible to other numerical value, such as can be 0.7
Or 0.9, invention is not limited thereto.
Step S52: according to the current imbalance rate of each user, the second set for determining stealing suspicion user is determined；
It specifically can be and judge whether the current imbalance rate of each user is greater than the second preset threshold, which can be
50%, when the current imbalance rate of user is greater than 50%, determine that user belongs to second set.In the other embodiment of the present invention
In, the second preset threshold is also possible to other numerical value, such as can be 40% or 60%, and invention is not limited thereto.
Step S53: according to first set and second set, stealing suspicion user is determined；It specifically can be according to the first collection
Conjunction and second set, determine the intersection of first set and second set, judge whether the intersection is empty set, when the intersection is not empty
When collection, determine that the user in intersection is stealing suspicion user, when the intersection is empty set, determines first set and second set
Union judges whether the union is empty set, when the union is not empty set, determines this and the user concentrated is stealing suspicion use
Family.
Fig. 6 shows another tool of the stealing intelligent diagnosing method in the embodiment of the present invention based on load characteristic model library
The exemplary flow chart of body, the historical load number that the embodiment of the present invention passes through collection power distribution station distribution transformer electric energy table and user's electric energy meter
Accordingly and the three-phase current data of user's electric energy meter, the correlation of user power utilization load with power distribution station management line loss is calculated
The current imbalance rate of coefficient and user power utilization, as load characteristic model library, not using electric current caused by electricity stealing
The features such as the strong correlation of balance, user power utilization load and unit-area management line loss carry out intelligence to electricity stealing in data plane and examine
It is disconnected, real-time analysis and the accurate positioning of stealing suspicion to user power utilization monitoring data are realized, compared to traditional artificial scene
Investigation method improves the efficiency of work of electricity anti-stealing and the accuracy of stealing suspicion positioning.
The stealing intelligent diagnostics equipment based on load characteristic model library that the embodiment of the invention also provides a kind of, such as Fig. 7 institute
Show, the electronic equipment may include processor 71 and memory 72, wherein processor 71 and memory 72 can by bus or
Person's other modes connect, in Fig. 7 for being connected by bus.
Processor 71 can be central processing unit (Central Processing Unit, CPU).Processor 71 can be with
For other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
The combination of the chips such as discrete hardware components or above-mentioned all kinds of chips.
Memory 72 is used as a kind of non-transient computer readable storage medium, can be used for storing non-transient software program, non-
Transient computer executable program and module, as the stealing based on load characteristic model library in the embodiment of the present invention is intelligently examined
The disconnected corresponding program instruction/module of method.Processor 71 is by running the non-transient software program being stored in memory 72, referring to
It enables and module is realized in above method embodiment thereby executing the various function application and data processing of processor
Stealing intelligent diagnosing method based on load characteristic model library.
Memory 72 may include storing program area and storage data area, wherein storing program area can storage program area,
Application program required at least one function；It storage data area can the data etc. that are created of storage processor 71.In addition, storage
Device 72 may include high-speed random access memory, can also include non-transient memory, for example, at least a magnetic disk storage
Part, flush memory device or other non-transient solid-state memories.In some embodiments, it includes relative to place that memory 72 is optional
The remotely located memory of device 71 is managed, these remote memories can pass through network connection to processor 71.The reality of above-mentioned network
Example includes but is not limited to internet, intranet, local area network, mobile radio communication and combinations thereof.
The detail of the above-mentioned stealing intelligent diagnostics equipment based on load characteristic model library can correspond to refering to fig. 1 to figure
Corresponding associated description and effect are understood that details are not described herein again in embodiment shown in 6.
It is that can lead to it will be understood by those skilled in the art that realizing all or part of the process in above-described embodiment method
Computer program is crossed to instruct relevant hardware and complete, the program can be stored in a computer-readable storage medium
In, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can for magnetic disk,
CD, read-only memory (Read-Only Memory, ROM), random access memory (Random Access
Memory, RAM), flash memory (Flash Memory), hard disk (Hard Disk Drive, abbreviation: HDD) or solid state hard disk
(Solid-State Drive, SSD) etc.；The storage medium can also include the combination of the memory of mentioned kind.
Although being described in conjunction with the accompanying the embodiment of the present invention, those skilled in the art can not depart from the present invention
Spirit and scope in the case where various modifications and variations can be made, such modifications and variations are each fallen within by appended claims institute
Within the scope of restriction.
Claims (13)
1. a kind of stealing intelligent diagnosing method based on load characteristic model library characterized by comprising
Obtain historical load number of the electric energy meter at multiple moment of distribution transformer electric energy table and the corresponding n user of the distribution transformer electric energy table
Three-phase current data according to the electric energy meter with the n user at the multiple moment, n are the integer more than or equal to 1；
It is negative in the history at multiple moment according to the distribution transformer electric energy table and the electric energy meter of the corresponding n user of the distribution transformer electric energy table
Lotus data obtain power distribution station in the management line loss at the multiple moment；
Historical load data and the distribution according to the electric energy meter of the corresponding n user of the distribution transformer electric energy table at multiple moment
Platform area obtains the corresponding historical load data of each user and the power distribution station in the management line loss at the multiple moment
Manage the relative coefficient of line loss；
Three-phase current data according to the electric energy meter of the n user at the multiple moment obtain the electric current of each user
Unbalance factor；
According to the relative coefficient of the corresponding historical load data of each user and the management line loss of the power distribution station and respectively
The current imbalance rate of the user determines stealing suspicion user.
2. stealing intelligent diagnosing method according to claim 1, which is characterized in that obtain the distribution by following formula
Management line loss of the platform area at the multiple moment:
Wherein, [L1, L2, L3..., Lm] indicate the management line loss of power distribution station moment 1 to the moment m, [dq1, dq2,
dq3..., dqm] indicate the historical load data of distribution transformer electric energy table moment 1 to the moment m, [q11, q21..., qn1] indicate when
Carve the historical load data of the electric energy meter of the 1 n user, [q12, q22..., qn2] indicate the moment 2 described in n user electricity
The historical load data of energy table, [q13, q23..., qn3] indicate the moment 3 described in n user electric energy meter historical load number
According to ..., [q1m, q2m..., qnm] indicate moment m described in n user electric energy meter historical load data.
3. stealing intelligent diagnosing method according to claim 2, which is characterized in that obtain each use by following formula
The relative coefficient of the corresponding historical load data in family and the management line loss of the power distribution station:
Wherein, [ρL1, ρL2, ρL3..., ρLn] respectively indicate the corresponding historical load data of the n user and the power distribution station
Management line loss relative coefficient, [q1i, q2i..., qni] indicate moment i described in n user electric energy meter historical load
Data,Indicate first user in the average value of the power load at m moment,Indicate second user m moment
The average value of power load ...,Indicate average value of the nth user in the power load at m moment, LiFor power distribution station
Management line loss in moment i,For power distribution station m moment average management line loss.
4. stealing intelligent diagnosing method according to any one of claim 1-3, which is characterized in that used according to described n
The electric energy meter at family obtains the current imbalance rate of each user in the three-phase current data at the multiple moment, comprising:
Three-phase current data according to the electric energy meter of the n user at the multiple moment respectively obtain each user and exist
The average value of the three-phase current at each moment；
According to the three-phase current data and each user in the average value of the three-phase current at each moment, obtain each described
Current imbalance rate of the user at each moment；
Current imbalance rate according to each user at each moment obtains the current imbalance rate of each user.
5. stealing intelligent diagnosing method according to claim 4, which is characterized in that obtain each use by following formula
Current imbalance rate of the family at each moment:
Wherein, imInmIndicate current imbalance rate of the nth user in moment m, iAnm、iBnmAnd iCnmIndicate nth user when
The three-phase current data of m are carved,Indicate three-phase current iAnm、iBnmAnd iCnmAverage value.
6. stealing intelligent diagnosing method according to claim 5, which is characterized in that obtain each use by following formula
The current imbalance rate at family:
Wherein, [imI1, imI2, imI3..., imIn] indicate the current imbalance rate of the n user, [imI11, imI12,
imI13..., imI1m] indicate current imbalance rate of the 1st user m moment, [imI21, imI22, imI23..., imI2m]
Indicate current imbalance rate of the 2nd user m moment, [imI31, imI32, imI33..., imI3m] indicate that the 3rd user exists
The current imbalance rate ..., [imI at m momentn1, imIn2, imIn3..., imInm] indicate nth user in the electricity at m moment
Flow unbalance factor.
7. stealing intelligent diagnosing method according to claim 1 to 6, which is characterized in that according to each user
The electric current of the relative coefficient and each user of corresponding historical load data and the management line loss of the power distribution station is uneven
Weighing apparatus rate determines stealing suspicion user, comprising:
According to the relative coefficient of each corresponding historical load data of user and the management line loss of the power distribution station, determine
For determining the first set of the stealing suspicion user；
According to the current imbalance rate of each user, the second set for determining the stealing suspicion user is determined；
According to the first set and the second set, the stealing suspicion user is determined.
8. stealing intelligent diagnosing method according to claim 7, which is characterized in that according to the corresponding history of each user
The relative coefficient of the management line loss of load data and the power distribution station, determination is for determining the of the stealing suspicion user
One set, comprising:
Judge the management line loss of the corresponding historical load data of each user and the power distribution station relative coefficient whether
Greater than the first preset threshold；
Described in being greater than when the relative coefficient of the corresponding historical load data of the user and the management line loss of the power distribution station
When the first preset threshold, determine that the user belongs to the first set.
9. stealing intelligent diagnosing method according to claim 8, which is characterized in that uneven according to the electric current of each user
Weighing apparatus rate determines the second set for determining the stealing suspicion user, comprising:
Judge whether the current imbalance rate of each user is greater than the second preset threshold；
When the current imbalance rate of the user is greater than second preset threshold, determine that the user belongs to second collection
It closes.
10. the stealing intelligent diagnosing method according to any one of claim 7-9, which is characterized in that according to described first
Set and the second set, determine the stealing suspicion user, comprising:
According to the first set and the second set, the intersection of the first set and the second set is determined；
Whether the intersection for judging the first set and the second set is empty set；
When the intersection of the first set and the second set is not empty set, determine the user in the intersection for institute
State stealing suspicion user.
11. stealing intelligent diagnosing method according to claim 10, which is characterized in that
When the intersection of the first set and the second set is empty set, the first set and the second set are determined
Union；
Whether the union for judging the first set and the second set is empty set；
When the union of the first set and the second set is not empty set, determine that the user that is described and concentrating is institute
State stealing suspicion user.
12. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage has computer to refer to
It enables, the computer instruction is for making the computer execute such as stealing intelligent diagnostics of any of claims 1-11
Method.
13. a kind of stealing intelligent diagnostics equipment based on load characteristic model library characterized by comprising memory and processing
Device communicates with each other connection between the memory and the processor, computer instruction, the place are stored in the memory
Device is managed by executing the computer instruction, thereby executing such as described in any item stealing intelligent diagnostics sides claim 1-11
Method.
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